Computational Engineering Expert

Cashback24x7; India; Remote; INR 2,066,000 - 3,168,000; Full time

Job summary

Cashback24x7 is seeking a Computational Engineering Expert to remotely contribute as a contractor. You will leverage deep expertise in CFD/FEA and simulation tools to shape AI benchmarking, evaluation, and real-world data integrity across multidisciplinary teams.

The role demands PhD-level or equivalent experience, strong communication, and the ability to translate complex domain knowledge into actionable insights for AI model improvement. Flexible, remote collaboration is expected.

Qualifications

• PhD or equivalent industry/research experience in computational, simulation, or systems engineering.
• Proven expertise in CFD, FEA, computational mechanics, robotics, control systems, or signal processing.
• Hands-on experience with simulation, analytical, or technical modeling tools (e.g., ANSYS, Abaqus, MATLAB, OpenFOAM).
• Strong problem-solving and systems-thinking skills, with a commitment to technical excellence.
• Exceptional written and verbal communication skills, enabling knowledge transfer and collaboration.
• Comfortable with scripting and scientific workflows in Python and/or MATLAB.

Responsibilities

• Inform AI benchmarking and evaluation processes with computational engineering insights.
• Analyze AI models’ performance in CFD/FEA and related engineering contexts.
• Review and enhance technical datasets, workflows, and simulation results for quality.
• Create written assessments and clearly communicate complex technical insights to the team.
• Collaborate with domain experts to identify gaps and opportunities for model improvement.
• Contribute to developing real-world benchmarks for AI systems in computational engineering.

Skills

CFD

FEA

Computational mechanics

Robotics

Control systems

Signal processing

Python

Education

PhD or equivalent

Tools

ANSYS

Abaqus

MATLAB

OpenFOAM

Job description

Job Title: Computational Engineering ExpertJob Type: ContractorLocation: RemoteJob Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Key Responsibilities

• Leverage your expertise in computational, simulation, or systems engineering to inform advanced AI benchmarking and evaluation processes.
• Analyze and provide feedback on AI models’ performance in realistic engineering scenarios related to CFD, FEA, robotics, and more.
• Review, assess, and enhance technical datasets, workflows, and simulation results for quality and accuracy.
• Utilize domain-specific tools such as ANSYS, Abaqus, COMSOL, OpenFOAM, and MATLAB to validate engineering solutions.
• Create detailed written assessments and communicate complex technical insights clearly with the team.
• Collaborate with a diverse group of domain experts to identify gaps and opportunities for AI model improvement.
• Contribute to the development of robust, real-world benchmarks for AI systems in computational engineering fields.

Required Skills and Qualifications

• PhD or equivalent industry/research experience in a computational, simulation, or systems engineering discipline.
• Proven expertise in areas such as CFD, FEA, computational mechanics, robotics, control systems, or signal processing.
• Hands-on experience with simulation, analytical, or technical modeling tools (e.g., ANSYS, Abaqus, MATLAB, OpenFOAM).
• Strong problem-solving and systems-thinking skills, with a commitment to technical excellence.
• Exceptional written and verbal communication skills, enabling clear knowledge transfer and collaborative work.
• Comfortable with scripting and scientific workflows in Python and/or MATLAB.
• Ability to synthesize complex domain knowledge into actionable insights for interdisciplinary teams.

Preferred Qualifications

• Experience applying AI/ML techniques within engineering domains or workflows.
• Familiarity with HPC, optimization, or large-scale simulation environments.
• Publication record, patents, or deep R&D involvement in computational engineering or simulation.